AMO / Quantum Information Physicist for AI Training

Role Overview

Apply advanced AMO physics and quantum information expertise to help train next-generation AI systems through research-focused benchmarking of quantum-optical concepts. The work focuses on cascaded optical parametric amplifiers, SU(1, 1) interferometers, loss effects, and two-mode squeezing. Assignments may be performed as a Solver, Auditor, or Adjudicator, based on your specialization, experience, and demonstrated hands-on capability.

Key Responsibilities

• Analyze and model cascaded optical parametric amplifiers and SU(1, 1) interferometric systems with realistic loss mechanisms.
• Apply Bogoliubov transformations and covariance-matrix methods to evaluate quantum correlations and noise properties.
• Derive and interpret sideband photocurrent spectra using homodyne detection methods.
• Implement and evaluate loss models using fictitious beamsplitters, benchmarking them against theoretical and experimental scenarios.
• Use squeeze-parameter hyperbolic identities to characterize entanglement and squeezing in lossy quantum systems.
• Provide high-quality subject-matter input that improves how AI systems learn, reason, and perform.

Qualifications

• Advanced degree, PhD or equivalent experience, in Atomic, Molecular, and Optical Physics, Quantum Optics, or Quantum Information Science.
• Demonstrated expertise in physics, Bogoliubov transformations, covariance-matrix formalism, and quantum noise analysis.
• Hands-on familiarity with sideband photocurrent spectra, homodyne detection, and quantum-optical loss modeling through fictitious beamsplitters.
• Experience applying squeeze-parameter hyperbolic identities in research or experimental analysis.
• Familiarity with cascaded parametric amplifiers, SU(1, 1) interferometry, or two-mode squeezing is highly valued.
• No previous AI experience is required.

Work Terms

• Remote contract engagement.

Compensation

• $80 to $160 per hour.